Data Science

Related Faculty

Morgan G. Ames

Morgan Ames

Alumni (MIMS 2006)
Assistant Professor of Practice
Science and technology studies; computer-supported cooperative work and social computing; education; anthropology; youth technocultures; ideology and inequity; critical data science
Daniel Aranki

Daniel Aranki

Assistant Professor of Practice
Predictive medicine; artificial intelligence; machine learning; tele-health; information disclosure; privacy; security.
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David Bamman

Associate Professor
Natural language processing, computational social science, machine learning, digital humanities
Coye Cheshire

Coye Cheshire

Professor
Trust, social exchange, social psychology, and information exchange
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John Chuang

Professor
Biosensory computing; climate informatics; information economics and policy

Recent Publications

Data Science news

Josh Blumenstock at the Artifical Intelligence for Economic Development conference
Josh Blumenstock Honored for Research in the Public Interest

Prof Blumenstock received the Faculty Award for Research in the Public Interest for his research at the intersection of machine learning and development economics.

Joshua Blumenstock
Joshua Blumenstock: The Knowns and Unknowns of Big Data and Poverty Alleviation

Joshua Blumenstock cautions that new digital methods of approaching issues of poverty must be used as a complement to more traditional approaches.

Josh Blumenstock
Josh Blumenstock Uses Phone Data to Reveal Socioeconomic Status
Anna Jacobson's data visualization "The Building Blocks of Gender Equality"
MIDS Student’s Feminist Visualization wins Data Science Challenge

“What would it mean to do feminist data science?” This question, raised by a fellow MIDS classmate, sparked the idea for Anna Jacobson’s award-winning data visualization “The Building Blocks of Gender Equality.”

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Big Data Meets Literary Analysis: Digital Humanities Research at the I School

Machine learning and big data don’t intuitively go hand-in-hand with studies of literary fiction; however, new research from Professor David Bamman, using a machine learning algorithm and natural language processing, revealed surprising trends related to gender in novels of the 20th century.  

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The Economist Explores David Bamman’s Algorithmic Literary Analysis
Image from The Big Sleep via The Guardian
The Guardian Notes David Bamman’s Findings on Representation of Women in Literature

Analysis from I School Professor David Bamman finds proportion of female authors and characters fell after 19th century, with male authors remaining ‘remarkably resistant’ to writing women.

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Big Data Reveals the Shrinking Role of Women in Novels

Professor David Bamman’s machine-learning algorithm analyzed the presentation of gender in more than 100,000 novels.

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School of Information Hiring New Professor in Human-Centered Data Science
Position will begin July 2016; applications are due December 14.
David Bamman
New Professor David Bamman is a Scholar of Computational Humanities and Social Sciences
Bamman’s work applies natural language processing and machine learning techniques to empirical questions in the humanities and social sciences.